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淡紫紫孢菌侵染烟粉虱的效应因子预测及其表达分析
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引用本文:官昭瑛,雷妍圆,许建新,张杰,HussinAbid,章玉苹.淡紫紫孢菌侵染烟粉虱的效应因子预测及其表达分析.植物保护学报,2026,53(3):669-678
DOI:10.13802/j.cnki.zwbhxb.2026.2026814
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作者单位E-mail
官昭瑛 深圳城市职业学院, 广东 深圳 518116  
雷妍圆 广东省农业科学院植物保护研究所, 广东省植物保护新技术重点实验室, 广州 510640 leiyanyuan@gdaas.cn 
许建新 深圳城市职业学院, 广东 深圳 518116  
张杰 深圳城市职业学院, 广东 深圳 518116  
HussinAbid 沙特阿拉伯环境、水和农业部, 利雅得 11442  
章玉苹 广东省农业科学院植物保护研究所, 广东省植物保护新技术重点实验室, 广州 510640  
中文摘要:为明确效应因子在淡紫紫孢菌Purpureocillium lilacinum致病过程中的作用,基于该菌已公布的全基因组信息,对其全部11 763个蛋白序列进行生物信息学分析以筛选候选效应因子,并通过实时荧光定量PCR技术分析候选效应因子在烟粉虱Bemisia tabaci不同发育阶段(卵、2龄若虫和雌成虫)的表达模式。结果显示:在11 763个蛋白序列中,利用SignalP 5.0软件预测获得1 072个含信号肽的蛋白;进一步通过TMHMM 2.0软件从中筛选出跨膜结构域少于2个的蛋白有1 048个;再经TargetP 2.0软件预测其中有1 044个蛋白的信号肽定位于分泌途径;最后通过ProtComp 9.0软件分析发现其中653个蛋白可能位于细胞外。从中筛选出半胱氨酸含量大于6的蛋白396个,通过T-Reks分析鉴定出119个蛋白具有串联重复序列,经病原物-寄主互作数据库注释,其中有43个蛋白获得功能信息。从中选取长度小于300个氨基酸的9个蛋白,根据突变表型预测筛选出8个与致病相关的潜在效应因子,其中6个效应因子的编码基因在烟粉虱雌成虫粗提物诱导下表达水平随时间升高,且雌成虫诱导效应强于2龄若虫和卵,尤以PlEF5PlEF8基因在48 h表达量最高,分别达对照的35.9倍和38.5倍;PlEF6基因在所有处理中均持续下调。表明淡紫紫孢菌对烟粉虱不同虫态的体表信号具有差异化响应,筛选出的效应因子可作为病原真菌-烟粉虱互作研究的关键靶点。
中文关键词:淡紫紫孢菌  烟粉虱  效应因子  生物信息学预测  时序表达分析
 
Prediction and expression analysis of effectors in Purpureocillium lilacinum infecting tobacco whitefly Bemisia tabaci
Author NameAffiliationE-mail
Guan Zhaoying Shenzhen City Polytechnic, Shenzhen 518116, Guangdong Province, China  
Lei Yanyuan Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Institute of Plant Protection, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, Guangdong Province, China leiyanyuan@gdaas.cn 
Xu Jianxin Shenzhen City Polytechnic, Shenzhen 518116, Guangdong Province, China  
Zhang Jie Shenzhen City Polytechnic, Shenzhen 518116, Guangdong Province, China  
Hussin Abid Ministry of Environment, Water and Agriculture, Riyadh 11442, Saudi Arabia  
Zhang Yuping Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Institute of Plant Protection, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, Guangdong Province, China  
Abstract:To clarify the role of effectors in the pathogenic process of Purpureocillium lilacinum against its insect host, candidate effectors were systematically predicted based on the published whole-genome information of this fungus. Bioinformatics analysis was performed on all 11 763 protein sequences to screen candidate effectors, and their expression patterns in response to crude extracts from different developmental stages of tobacco whitefly Bemisia tabaci(eggs, second-instar nymphs and female adults) were analyzed by real-time quantitative PCR. The results showed that 1 072 proteins containing signal peptides were predicted using SignalP 5.0; 1 048 proteins with fewer than two transmembrane domains were further screened using TMHMM 2.0; TargetP 2.0 predicted that the signal peptides of 1 044 proteins were localized to the secretory pathway; and ProtComp 9.0 indicated that 653 proteins were potentially extracellular. Among these proteins, 396 had more than six cysteine residues, 119 contained tandem repeats according to T-Reks analysis, and 43 were functionally annotated in the pathogenhost interaction database. Nine proteins shorter than 300 amino acids were selected, and eight potential pathogenicity-related effectors were predicted based on mutant phenotypes. Among them, the coding genes of six effectors showed increased expression over time under induction by crude extracts of B. tabaci female adults, and the induction effect of female adults was stronger than that of 2 nd-instar nymphs and eggs. In particular, PlEF5 and PlEF8 exhibited the highest expression levels at 48 h(35.9-and 38.5-fold that of the control, respectively). In contrast, PlEF6 was continuously downregulated in all treatments. These results indicate that P. lilacinum responds differentially to surface signals from different developmental stages of B. tabaci, and the screened effectors may serve as key targets for further research on pathogen fungus-B. tabaci interactions.
keywords:Purpureocillium lilacinum  Bemisia tabaci  effectors  bioinformatics prediction  temporal expression analysis
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